class_docstr: A Model is a network (more precisely, a directed acyclic graph) of Steps,
  and it is defined from the input/output specification of the pipeline.
  Models have fit and predict routines that, together with graph-based engine,
  allow the automatic (feed-forward) computation of each of the pipeline steps
  when fed with data.
  
  Parameters
  ----------
  inputs
      Inputs to the model.
  
  outputs
      Outputs of the model.
  
  targets
      Targets of the model.
  
  name
      Name of the model (optional). If no name is passed, a name will be
      automatically generated.
docstr: Get a step (graph node) in the model by name.
  
  Parameters
  ----------
  name
      Name of the step.
  
  Returns
  -------
  The step.
docstr_tok: ["Get","a","step","(","graph","node",")","in","the","model","by","name",".","Parameters","--","--","--","--","--","name","Name","of","the","step",".","Returns","--","--","--","-","The","step","."]
code: def get_step(self, name: str) -> Step:
      """Get a step (graph node) in the model by name.
  
      Parameters
      ----------
      name
          Name of the step.
  
      Returns
      -------
      The step.
      """
      # Steps are assumed to have unique names (guaranteed by success of build_graph_from_outputs)
      if name in self._steps.keys():
          return self._steps[name]
      raise ValueError("{} was not found in the model.".format(name))
  
imports: from collections import defaultdict
  from typing import Union, List, Dict, Set, Iterable, Optional
  from baikal._core.data_placeholder import is_data_placeholder_list, DataPlaceholder
  from baikal._core.digraph import DiGraph
  from baikal._core.step import Step, InputStep, Node
  from baikal._core.typing import ArrayLike
  from baikal._core.utils import listify, safezip2, SimpleCache, unlistify
label_desc: Use image node_id 7 for calling the Model obj's underlying member method code with example usage: obj.get_step(name) and returns: self